To strengthen the governance of and programmatic and administrative support for Multilateral Environmental Agreements (MEAs) by United Nations organizations by identifying measures to promote enhanced coordination, coherence and synergies between MEAs and the United Nations system, thus increasing United Nations system's contribution towards a more integrated approach to international environmental governance and management at national, regional and international levels.Available onlineCall Number: [EL]Physical Description: 49 p.

A global outlook and outcome of the Environmental Governance programme cycle

Yearly citation counts for the publication titled "Scale, Sovereignty, and Strategy in Environmental Governance".

The World Bank's ESG Data Draft dataset provides information on 17 key sustainability themes spanning environmental, social, and governance categories. In order to shift financial flows so that they are better aligned with global goals, the World Bank Group (WBG) is working to provide financial markets with improved data and analytics that shed light on countries’ sustainability performance. Along with new information and tools, the World Bank will also develop research on the correlation between countries’ sustainability performance and the risk and return profiles of relevant investments.

How do political authorities in China respond to mounting environmental problems? Moreover, on what basis do they succeed in securing public approval in the realm of environmental governance? In this study, I argue that local authorities perform "symbolic responsiveness" as a strategy to manage public opinion over environmental issues. Furthermore, symbolic responsiveness is effective in generating public approval, despite the lack of, and sometimes at the expense of appreciable improvement in environmental quality. Data collected in 2014-2015.

Policy actors address complex environmental problems by engaging in multiple and often interdependent policy issues. Policy issue interdependencies imply that efforts by actors to address separate policy issues can either reinforce (‘win-win’) or counteract (‘trade-off’) each other. Thus, if interdependent issues are managed in isolation instead of being coordinated, the most effective and well-balanced solution to the underlying problem might never be realised. This study asks if reinforcing and counteracting interdependencies have different impacts on perception and collaboration. Our empirical study of collaborative water governance in the Norrström basin, Sweden, shows that policy actors often avoid collaborating when the policy issues exhibit reinforcing interdependencies. Our evidence indicates a perceived infeasibility of acting on reinforcing interdependencies. We also find that actors do not consider counteracting interdependencies (‘trade-offs’) at all when they engage in collaboration. Further, even though actors were aware of counteracting and reinforcing interdependencies, our analyses suggest they might be less aware of the former. These findings illustrate that actors either avoid each other due to policy issue interdependencies or, at best, ignore existing interdependencies when engaging in collaboration. Our study highlights the importance of problem perception in accomplishing integrated solutions to complex environmental problems, and of how understandings of different types of interdependencies shape collaboration in environmental governance.

This dataset consists of social network analysis data and policy issue network data. Network data consists of nodes (rows and columns) and links (matrix cells). In the social network data, rows and columns represent actors and matrix cells their collaboration. 1 indicates collaboration, 0 indicates no collaboration. In the policy issue network data, rows and columns represent policy issues, and matrix cells their reinforcing or counteracting interdependencies. Two different policy issue networks (one reinforcing and one counteracting) are represented. The actor-issue file reports the engagement of an actor in a given issue, i.e. that the actor works with that specific issue. The data also includes an actor attribute file, where each row represents the same actor as in the social network data and each column a specific attribute that might characterise the actor (1-yes,0-no). The data files are compatible with the free software MpNet (http://www.melnet.org.au/pnet), and for running Exponential Random Graph Models.

For more information see: Hedlund, J., Nohrstedt, D., Morrison, T. et al. Challenges for environmental governance: policy issue interdependencies might not lead to collaboration. Sustain Sci (2022). DOI: https://doi.org/10.1007/s11625-022-01145-8

The 2000 Pilot Environmental Sustainability Index (ESI) is an exploratory effort to construct an index that measures the ability of a nation's economy to achieve sustainable development, with the long term goal of finding a single indicator for environmental sustainability analagous to that of the Gross Domestic Product (GDP). The index covering 56 countries is a composite measure of the current status of a nation's environmental systems, pressures on those systems, human vulnerability to environmental change, national capacity to respond, and contributions to global environmental stewardship. The index was unveiled at the World Economic Forum's annual meeting, January 2000, Davos, Switzerland. The 2000 Pilot ESI is the result of collaboration among the World Economic Forum (WEF), Yale Center for Environmental Law and Policy (YCELP), and the Columbia University Center for International Earth Science Information Network (CIESIN).

Self-administered questionnaireSelf-administered questionnaire

In many communities, regions, or landscapes, there are numerous environmental groups working across different sectors and creating stewardship networks that shape the environment and the benefits people derive from it. The make-up of these networks can vary, but generally include organizations of different sizes and capacities. As the Covid-19 pandemic (2020 to the present) shuts down businesses and nonprofits, catalyzes new initiatives, and generally alters the day-to-day professional and personal lives, it is logical to assume that these stewardship networks and their environmental work are impacted; exactly how, is unknown. In this study, we analyze the self-reported effects of the Covid-19 pandemic on stewardship groups working in southeast New England, USA. Stewardship organizations were surveyed from November 2020 to April 2021 and asked, among other questions, “How is Covid-19 affecting your organization?” We analyzed responses using several qualitative coding approaches. Our analysis revealed group-level impacts including changes in group capacity, challenges in managing access to public green spaces, and altered forms of volunteer engagement. These results provide insights into the varied effects of the Covid-19 pandemic and government responses such as stay-at-home orders and social distancing policies on stewardship that can inform the development of programs to reduce negative outcomes and enhance emerging capacities and innovations.

1. Collaborative approaches to environmental governance are drawing increased interest in research and practice. In this article we investigate the structure and functioning of actor networks engaged in collaboration.

2. We specifically seek to advance understanding of how and why collaborative networks are formed as actors engage in addressing two broad classes of collective action problems: coordination and cooperation. It has been proposed that more risk-prone cooperative problems favor denser and more cohesive bonding network structures, whereas less risky coordination problems favor sparser and more centralized bridging structures.

3. Recent empirical findings however cast some doubts on these assumptions. In building on previous work we propose and evaluate a set of propositions in order to remedy these ambiguities. Our propositions build on the assumption that bridging structures could, if actors’ experience sufficient levels of trust in the collaborative process, adequately support both cooperation and coordination problems.

4. Our empirical investigation of four UNESCO’s Man and Biosphere Reserves gives initial support for our assumptions, and suggest that bridging structures emerge when actors have trust in the collaborative endeavor, and/or when the cost of collaborative failure is deemed low. While caution is warranted due to data limitations, our findings contribute to improved policies and guidelines on how to stimulate and facilitate more effective collaborative approaches to environmental governance.

The dataset contains four networks (one per MAB reserve). The data is further described in the published paper. For each network, there are several files. The files are formatted for the program MPnet. One file per network is the sociomatrix (rows and columns are nodes, and the values in the matrix are the links between the nodes). Several other files, per network, contain node attributes (further described in the published paper). The order of the node attributes are the same as in the sociomatrices.

The 2002 Environmental Sustainability Index (ESI) measures overall progress toward environmental sustainability for 142 countries based on environmental systems, stresses, human vulnerability, social and institutional capacity and global stewardship. The addition of a climate change indicator, reduction in number of capacity indicators, and an improved imputation methodology contributed to an improvement from the 2001 ESI. The index was unveiled at the World Economic Forum's annual meeting, January 2002, New York. The 2002 ESI is the result of collaboration among the World Economic Forum (WEF), Yale Center for Environmental Law and Policy (YCELP), and the Columbia University Center for International Earth Science Information Network (CIESIN).

United States Environmental Policy Stringency Index data was reported at 3.028 NA in 2020. This records an increase from the previous number of 2.917 NA for 2019. United States Environmental Policy Stringency Index data is updated yearly, averaging 1.250 NA from Dec 1990 (Median) to 2020, with 31 observations. The data reached an all-time high of 3.028 NA in 2020 and a record low of 0.833 NA in 1991. United States Environmental Policy Stringency Index data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s United States – Table US.OECD.ESG: Environmental: Environmental Policy Stringency Index: OECD Member: Annual.

Actor-Issue Edgelist

We lack an understanding of how diverse policymakers interact to govern biodiversity. Taking Colombia as a focal case, we asked: (i) What is the composition of today’s policy mix?; (ii) How has the policy mix evolved over time?; (iii) How do policies differ among actors and ecosystems?; and (iv) Does the policy mix address the primary threats to biodiversity? We found 186 biodiversity-related policies that govern multiple ecosystems, use different instruments, and evolve as a mix to address the main threats to biodiversity (i.e., agriculture and aquaculture, biological resource use). We notice policy gaps in the governance of invasive species. Biodiversity policy integration into some sectoral policies, such as climate change and pollution, has become more common in the past decade. Our results point to an increased need for effective coordination across sectors and actors, as new ones become part of the policy mix.

The 2018 Environmental Performance Index (EPI) ranks 180 countries on 24 performance indicators in the following 10 issue categories: air quality, water and sanitation, heavy metals, biodiversity and habitat, forests, fisheries, climate and energy, air pollution, water resources, and agriculture. These categories track performance and progress on two broad policy objectives, environmental health and ecosystem vitality. The EPI's proximity-to-target methodology facilitates cross-country comparisons among economic and regional peer groups. The data set includes the 2018 EPI, component scores, and time-series source data. The 2018 EPI was formally released in Davos, Switzerland, at the annual meeting of the World Economic Forum in January 2018. It is the result of collaboration of the Yale Center for Environmental Law and Policy (YCELP), Yale University, Columbia University Center for International Earth Science Information Network (CIESIN), and the World Economic Forum (WEF). The Interactive Website for the 2018 EPI is at https://epi.envirocenter.yale.edu/.

The 2020 Environmental Performance Index (EPI) ranks 180 countries on 32 performance indicators in the following 11 issue categories: air quality, sanitation and drinking water, heavy metals, waste management, biodiversity and habitat, ecosystem services, fisheries, climate change, pollution emissions, agriculture, and water resources. These categories track performance and progress on two broad policy objectives, environmental health and ecosystem vitality. The EPI's proximity-to-target methodology facilitates cross-country comparisons among economic and regional peer groups. The data set includes the 2020 EPI, component scores, and time-series source data. It is the result of a collaboration of the Yale Center for Environmental Law and Policy (YCELP), Yale University, and the Columbia University Center for International Earth Science Information Network (CIESIN). The Interactive Website for the 2020 EPI is at https://epi.yale.edu/.

Based on the panel data of environmental Non-Governmental Organizations (ENGOs) and air pollution in OECD countries, this paper uses econometric model to investigate the governance effect of ENGOs on air pollution. The results show that: ENGOs have a positive impact on the improvement of environmental quality, and the results are still valid after a series of robustness tests; Further mechanism analysis found that the environmental improvement by ENGOs is mainly achieved by increasing investment in environmental protection. This study provides empirical evidence for the effect of ENGOs on air pollution, and further provides ideas for environmental governance.

The Compendium of Environmental Sustainability Indicator Collections, Version 1.1 contains 426 indicators for 239 countries from five major environmental sustainability indicator efforts: the 2006 Environmental Performance Index (EPI), 2005 Environmental Sustainability Index (ESI), 2004 Environmental Vulnerability Index (EVI), the Rio to Johannesburg Dashboard, the Wellbeing of Nations, and 2006 National Footprint Accounts. It also incorporates 38 ancillary variables such as region name, dummy variables for landlocked countries and small island states, population, GDP, and land area. The collection is compiled and distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).

The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) provides a framework for the collation of a consistent set of climate impact data across sectors and scales. It also provides a unique opportunity for considering interactions between climate change impacts across sectors through consistent scenarios.
The ISIMIP3a part of the third simulation round is dedicated to i) impact model evaluation and improvement and ii) detection and attribution of observed impacts according to the framework of IPCC AR5 Working Group II Chapter 18. To this end all simulations are driven by observed socio-economic information combined with either observed (factual) climate data or a detrended (counterfactual) version of the observed climate allowing for the generation of a “no climate change” baseline.
This data set provides annual maps of various land use categories. In particular it gives annual maps of both rainfed and irrigated areas of total croplands, of 5 crop categories (C3 annual, C3 perennial, C4 annual, C4 perennial and C3 nitrogen fixing crops) and of 15 crop types/categories (C3 annual disaggregated into: rapeseed, rice, temperate cereals, temperate roots, tropical roots, sunflower, others C3 annual; C3 perennial: (no further disaggregation); C3 nitrogen-fixing disaggregated into: groundnut, pulses, soybean, others C3 nitrogen-fixing; C4 annual disaggregated into: maize, tropical cereals; C4 perennial: sugarcane). Furthermore, maps of pastures, managed rangelands and urban areas are provided.
Data is available for the historical time period: 1850-2021.
Version 1.1 of this dataset adds the 1901soc scenario with fixed year-1901 direct human influences.
Version 1.2 adds data for the years 2020 and 2021.